pandas.MultiIndex.sortlevel#
- MultiIndex.sortlevel(level=0, ascending=True, sort_remaining=True, na_position='first')[source]#
Sort MultiIndex at the requested level.
The result will respect the original ordering of the associated factor at that level.
- Parameters:
- levellist-like, int or str, default 0
If a string is given, must be a name of the level. If list-like must be names or ints of levels.
- ascendingbool, default True
False to sort in descending order. Can also be a list to specify a directed ordering.
- sort_remainingsort by the remaining levels after level
- na_position{‘first’ or ‘last’}, default ‘first’
Argument ‘first’ puts NaNs at the beginning, ‘last’ puts NaNs at the end.
New in version 2.1.0.
- Returns:
- sorted_indexpd.MultiIndex
Resulting index.
- indexernp.ndarray[np.intp]
Indices of output values in original index.
Examples
>>> mi = pd.MultiIndex.from_arrays([[0, 0], [2, 1]]) >>> mi MultiIndex([(0, 2), (0, 1)], )
>>> mi.sortlevel() (MultiIndex([(0, 1), (0, 2)], ), array([1, 0]))
>>> mi.sortlevel(sort_remaining=False) (MultiIndex([(0, 2), (0, 1)], ), array([0, 1]))
>>> mi.sortlevel(1) (MultiIndex([(0, 1), (0, 2)], ), array([1, 0]))
>>> mi.sortlevel(1, ascending=False) (MultiIndex([(0, 2), (0, 1)], ), array([0, 1]))